Integration of genetics and miRNA–target gene network identified disease biology implicated in tissue specificity. Issue 22 (8th November 2018)

• Record Type: Journal Article
• Authors: Sakaue, Saori; Hirata, Jun; Maeda, Yuichi; Kawakami, Eiryo; Nii, Takuro; Kishikawa, Toshihiro; Ishigaki, Kazuyoshi; Terao, Chikashi; Suzuki, Ken; Akiyama, Masato; Suita, Naomasa; Masuda, Tatsuo; Ogawa, Kotaro; Yamamoto, Kenichi; Saeki, Yukihiko; Matsushita, Masato; Yoshimura, Maiko; Matsuoka, Hidetoshi; Ikari, Katsunori; Taniguchi, Atsuo; Yamanaka, Hisashi; Kawaji, Hideya; Lassmann, Timo; Itoh, Masayoshi; Yoshitomi, Hiroyuki; Ito, Hiromu; Ohmura, Koichiro; R Forrest, Alistair R; Hayashizaki, Yoshihide; Carninci, Piero; Kumanogoh, Atsushi; Kamatani, Yoichiro; de Hoon, Michiel; Yamamoto, Kazuhiko; Okada, Yukinori;
• Is Part Of: Nucleic acids research. Volume 46:Issue 22(2018)
• Page Start: 11898
• Page End: 11909
• Publication Date: 2018-11-08
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gky1066
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: MicroRNAs (miRNAs) modulate the post-transcriptional regulation of target genes and are related to biology of complex human traits, but genetic landscape of miRNAs remains largely unknown. Given the strikingly tissue-specific miRNA expression profiles, we here expand a previous method to quantitatively evaluate enrichment of genome-wide association study (GWAS) signals on miRNA–target gene networks (MIGWAS) to further estimate tissue-specific enrichment. Our approach integrates tissue-specific expression profiles of miRNAs (∼1800 miRNAs in 179 cells) with GWAS to test whether polygenic signals enrich in miRNA–target gene networks and whether they fall within specific tissues. We applied MIGWAS to 49 GWASs ( n Total = 3 520 246), and successfully identified biologically relevant tissues. Further, MIGWAS could point miRNAs as candidate biomarkers of the trait. As an illustrative example, we performed differentially expressed miRNA analysis between rheumatoid arthritis (RA) patients and healthy controls ( n = 63). We identified novel biomarker miRNAs (e.g. hsa-miR-762) by integrating differentially expressed miRNAs with MIGWAS results for RA, as well as novel associated loci with significant genetic risk (rs56656810 at MIR762 at 16q11; n = 91 482, P = 3.6 × 10 −8 ). Our result highlighted that miRNA–target gene network contributes to human disease genetics in a cell type-specific manner, which could yield an efficient screening of miRNAs as promising biomarkers.